1d0aa7f57e
Model: W-61/llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.45-s_star-0.3-20260428-045924 Source: Original Platform
library_name, base_model, tags, datasets, model-index
| library_name | base_model | tags | datasets | model-index | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | W-61/llama-3-8b-base-sft-ultrachat-8xh200 |
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llama-3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.45-s_star-0.3-20260428-045924
This model is a fine-tuned version of W-61/llama-3-8b-base-sft-ultrachat-8xh200 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.6247
- Fcm Dpo/beta: 0.0013
- Margin Dpo/margin Mean: 159.3335
- Margin Dpo/margin Std: 334.4711
- Logps/chosen: -719.7628
- Logps/rejected: -858.1997
- Logps/ref Chosen: -287.8268
- Logps/ref Rejected: -266.9300
- Kl/chosen Kl Mean: -431.9361
- Kl/rejected Kl Mean: -591.2697
- Kl/mean: -511.6028
- Kl/std: 291.8582
- Logits/chosen: -0.7614
- Logits/rejected: -0.7369
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Fcm Dpo/beta | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Kl/chosen Kl Mean | Kl/rejected Kl Mean | Kl/mean | Kl/std | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4.9611 | 0.4188 | 200 | 0.6006 | 0.0042 | 62.7416 | 107.9594 | -420.2400 | -462.0849 | -287.8268 | -266.9300 | -132.4133 | -195.1548 | -163.7841 | 96.7906 | -0.8913 | -0.8725 |
| 4.9672 | 0.8377 | 400 | 0.6247 | 0.0013 | 159.3335 | 334.4711 | -719.7628 | -858.1997 | -287.8268 | -266.9300 | -431.9361 | -591.2697 | -511.6028 | 291.8582 | -0.7614 | -0.7369 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4